Devices like digital cameras, film scanners, x-ray machines, and radar imaging devices typically introduce noise into the resulting image. The noise can result from a variety of sources, including sampling errors, temperature-induced “dark current” noise, amplifier noise, and grain in scanned film images. The noise may appear as grain, speckles, and other artifacts. When the amount of noise is sufficiently high, it can detract significantly from the quality of the image, and so it is desirable to remove it.
With many devices, noise is not constant across the image. For instance, well-illuminated areas might have very little noise, while deep shadows may exhibit obvious noise artifacts. The relationship between noise and factors like image brightness is unique for every type of device.
Published methods for characterizing noise and for removing or reducing it typically assume that noise is a function of image luminance and/or spatial frequency.
However, this is insufficient to accurately describe the noise for some devices. In particular, noise may be jointly dependent on luminance, color, and frequency.
U.S. Pat. Nos. 6,256,403 and 6,069,982 disclose methods for characterizing noise in digital imaging devices. In U.S. Pat. No. 6,256,403, the method is applied to grayscale medical images, and the noise in the image is characterized only in relationship to luminance. This patent does not appear to consider that noise might vary with factors other than luminance.
U.S. Pat. No. 6,069,982 pertains to color imaging devices. For each channel of a color space, noise is characterized using a two-dimensional power spectrum (called a “noise mask”), and the noise variance in is also separately related to luminance. This patent appears to relate noise only to gray-scale levels. So, this method may not accurately characterize noise that is dependent on both luminance and color.